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ortools-clone/examples/cpp/binpacking_2d_sat.cc
Laurent Perron cce9c57758 fix examples
2022-03-25 10:07:27 +01:00

237 lines
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C++

// Copyright 2010-2021 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// This file solves a 2D Bin Packing problem.
// It loads the size of the main rectangle, all available items (rectangles
// too), and tries to fit all rectangles in the minimum numbers of bins (they
// have the size of the main rectangle.)
#include <algorithm>
#include <cstdint>
#include <limits>
#include <string>
#include <vector>
#include "absl/flags/flag.h"
#include "google/protobuf/text_format.h"
#include "ortools/base/commandlineflags.h"
#include "ortools/base/init_google.h"
#include "ortools/base/logging.h"
#include "ortools/packing/binpacking_2d_parser.h"
#include "ortools/packing/multiple_dimensions_bin_packing.pb.h"
#include "ortools/sat/cp_model.h"
ABSL_FLAG(std::string, input, "", "Input file.");
ABSL_FLAG(int, instance, -1, "Instance number if the file.");
ABSL_FLAG(std::string, params, "", "Sat parameters in text proto format.");
ABSL_FLAG(int, max_bins, 0,
"Maximum number of bins. The 0 default value implies the code will "
"use some heuristics to compute this number.");
ABSL_FLAG(bool, symmetry_breaking, true, "Use symmetry breaking constraints");
ABSL_FLAG(bool, global_area_constraint, false,
"Redundant constraint to link the global area covered");
ABSL_FLAG(bool, alternate_model, true,
"A different way to express the objective");
namespace operations_research {
namespace sat {
// Load a 2D binpacking problem and solve it.
void LoadAndSolve(const std::string& file_name, int instance) {
packing::BinPacking2dParser parser;
if (!parser.Load2BPFile(file_name, instance)) {
LOG(FATAL) << "Cannot read instance " << instance << " from file '"
<< file_name << "'";
}
packing::MultipleDimensionsBinPackingProblem problem = parser.problem();
LOG(INFO) << "Successfully loaded instance " << instance << " from file '"
<< file_name << "'";
LOG(INFO) << "Instance has " << problem.items_size() << " items";
const auto box_dimensions = problem.box_shape().dimensions();
const int num_dimensions = box_dimensions.size();
const int num_items = problem.items_size();
const int64_t area_of_one_bin = box_dimensions[0] * box_dimensions[1];
int64_t sum_of_items_area = 0;
for (const auto& item : problem.items()) {
CHECK_EQ(1, item.shapes_size());
const auto& shape = item.shapes(0);
CHECK_EQ(2, shape.dimensions_size());
sum_of_items_area += shape.dimensions(0) * shape.dimensions(1);
}
// Take the ceil of the ratio.
const int64_t trivial_lb =
(sum_of_items_area + area_of_one_bin - 1) / area_of_one_bin;
LOG(INFO) << "Trivial lower bound of the number of bins = " << trivial_lb;
const int max_bins = absl::GetFlag(FLAGS_max_bins) == 0
? trivial_lb * 2
: absl::GetFlag(FLAGS_max_bins);
if (absl::GetFlag(FLAGS_max_bins) == 0) {
LOG(INFO) << "Setting max_bins to " << max_bins;
}
CpModelBuilder cp_model;
// We do not support multiple shapes per item.
for (int item = 0; item < num_items; ++item) {
const int num_shapes = problem.items(item).shapes_size();
CHECK_EQ(1, num_shapes);
}
// Create one Boolean variable per item and per bin.
std::vector<std::vector<BoolVar>> item_to_bin(num_items);
for (int item = 0; item < num_items; ++item) {
item_to_bin[item].resize(max_bins);
for (int b = 0; b < max_bins; ++b) {
item_to_bin[item][b] = cp_model.NewBoolVar();
}
}
// Exactly one bin is selected for each item.
for (int item = 0; item < num_items; ++item) {
cp_model.AddEquality(LinearExpr::Sum(item_to_bin[item]), 1);
}
// Manages positions and sizes for each item.
std::vector<std::vector<std::vector<IntervalVar>>>
interval_by_item_bin_dimension(num_items);
for (int item = 0; item < num_items; ++item) {
interval_by_item_bin_dimension[item].resize(max_bins);
for (int b = 0; b < max_bins; ++b) {
interval_by_item_bin_dimension[item][b].resize(2);
for (int dim = 0; dim < num_dimensions; ++dim) {
const int64_t dimension = box_dimensions[dim];
const int64_t size = problem.items(item).shapes(0).dimensions(dim);
const IntVar start = cp_model.NewIntVar({0, dimension - size});
interval_by_item_bin_dimension[item][b][dim] =
cp_model.NewOptionalFixedSizeIntervalVar(start, size,
item_to_bin[item][b]);
}
}
}
// Non overlapping.
if (num_dimensions == 1) {
LOG(FATAL) << "One dimension is not supported.";
} else if (num_dimensions == 2) {
LOG(INFO) << "Box size: " << box_dimensions[0] << "*" << box_dimensions[1];
for (int b = 0; b < max_bins; ++b) {
NoOverlap2DConstraint no_overlap_2d = cp_model.AddNoOverlap2D();
for (int item = 0; item < num_items; ++item) {
no_overlap_2d.AddRectangle(interval_by_item_bin_dimension[item][b][0],
interval_by_item_bin_dimension[item][b][1]);
}
}
} else {
LOG(FATAL) << num_dimensions << " dimensions not supported.";
}
// Redundant constraint.
// The sum of areas in each bin is the sum of all items area.
if (absl::GetFlag(FLAGS_global_area_constraint)) {
LinearExpr sum_of_areas;
for (int item = 0; item < num_items; ++item) {
const int64_t item_area = problem.items(item).shapes(0).dimensions(0) *
problem.items(item).shapes(0).dimensions(1);
for (int b = 0; b < max_bins; ++b) {
sum_of_areas += item_to_bin[item][b] * item_area;
}
}
cp_model.AddEquality(sum_of_areas, sum_of_items_area);
}
if (absl::GetFlag(FLAGS_alternate_model)) {
const IntVar obj = cp_model.NewIntVar(Domain(trivial_lb, max_bins));
cp_model.Minimize(obj);
for (int b = trivial_lb; b < max_bins; ++b) {
for (int item = 0; item < num_items; ++item) {
cp_model.AddGreaterOrEqual(obj, b + 1)
.OnlyEnforceIf(item_to_bin[item][b]);
}
}
} else {
// Maintain one Boolean variable per bin that indicates if the bin is used
// or not.
std::vector<BoolVar> bin_is_used(max_bins);
for (int b = 0; b < max_bins; ++b) {
bin_is_used[b] = cp_model.NewBoolVar();
// Link bin_is_used[i] with the items in bin i.
std::vector<BoolVar> all_items_in_bin;
for (int item = 0; item < num_items; ++item) {
cp_model.AddImplication(item_to_bin[item][b], bin_is_used[b]);
all_items_in_bin.push_back(item_to_bin[item][b]);
}
cp_model.AddBoolOr(all_items_in_bin).OnlyEnforceIf(bin_is_used[b]);
}
// Symmetry breaking.
if (absl::GetFlag(FLAGS_symmetry_breaking)) {
// Forces the number of items per bin to decrease.
std::vector<IntVar> num_items_in_bin(max_bins);
for (int b = 0; b < max_bins; ++b) {
num_items_in_bin[b] = cp_model.NewIntVar({0, num_items});
std::vector<BoolVar> items_in_bins;
for (int item = 0; item < num_items; ++item) {
items_in_bins.push_back(item_to_bin[item][b]);
}
cp_model.AddEquality(num_items_in_bin[b],
LinearExpr::Sum(items_in_bins));
}
for (int b = 1; b < max_bins; ++b) {
cp_model.AddGreaterOrEqual(num_items_in_bin[b - 1],
num_items_in_bin[b]);
}
}
// Objective.
cp_model.Minimize(LinearExpr::Sum(bin_is_used));
}
// Setup parameters.
SatParameters parameters;
parameters.set_log_search_progress(true);
parameters.set_use_timetabling_in_no_overlap_2d(true);
parameters.set_use_energetic_reasoning_in_no_overlap_2d(true);
// Parse the --params flag.
if (!absl::GetFlag(FLAGS_params).empty()) {
CHECK(google::protobuf::TextFormat::MergeFromString(
absl::GetFlag(FLAGS_params), &parameters))
<< absl::GetFlag(FLAGS_params);
}
// We rely on the solver default logging to log the number of bins.
const CpSolverResponse response =
SolveWithParameters(cp_model.Build(), parameters);
}
} // namespace sat
} // namespace operations_research
int main(int argc, char** argv) {
absl::SetFlag(&FLAGS_logtostderr, true);
InitGoogle(argv[0], &argc, &argv, true);
if (absl::GetFlag(FLAGS_input).empty()) {
LOG(FATAL) << "Please supply a data file with --input=";
}
if (absl::GetFlag(FLAGS_instance) == -1) {
LOG(FATAL) << "Please supply a valid instance number with --instance=";
}
operations_research::sat::LoadAndSolve(absl::GetFlag(FLAGS_input),
absl::GetFlag(FLAGS_instance));
return EXIT_SUCCESS;
}